Dataset of Tactile Signatures of the Human Right Hand in Twenty-One Activities of Daily Living Using a High Spatial Resolution Pressure Sensor

Abstract

Successful grasping with multi-fingered prosthetic or robotic hands remains a challenge to be solved for the effective use of these hands in unstructured environments. To this end, currently available tactile sensors need to improve their sensitivity, robustness, and spatial resolution, but a better knowledge of the distribution of contact forces in the human hand in grasping tasks is also necessary. The human tactile signatures can inform models for an efficient control of the artificial hands. In this study we present and analyze a dataset of tactile signatures of the human hand in twenty-one representative activities of daily living, obtained using a commercial high spatial resolution pressure sensor. The experiments were repeated for twenty-two subjects. The whole dataset includes more than one hundred million pressure data. The effect of the task and the subject on the grip force and the contribution to this grip force made by the different hand regions were analyzed. We also propose a method to effectively synchronize the measurements from different subjects and a method to represent the tactile signature of each task, highlighting the hand regions mainly involved in the task. The correlations between hand regions and between different tasks were also analyzed.

Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product Manipulation

“…This can be observed in sensor activation in tasks A1, A3, and A4 (all requiring power grasps), where additional palm sensors detected grasp or release. These results are consistent with previous studies analyzing hand pressure distribution in activities of daily living [15]. The only important difference regarding the results in the literature was the inactivity observed for pressure sensor s10.…”

“…The only important difference regarding the results in the literature was the inactivity observed for pressure sensor s10. This palm spot was observed to present a higher activation of pressure sensors in [15] but this may be attributable to the pressure sensor size, as the used in previous studies was almost thrice the size of VMG30 sensors. The second spot observed to have higher activation in the aforementioned study was distal phalanx of index finger, which is consistent with the results here obtained using VMG30. ))…”

“…For this reason, a VMG30 glove (Figure 1) was acquired by our research group but customized with five extra pressure sensors on the palm and the proximal phalanx of the middle finger. The customization of the glove and the location of the five extra sensors was motivated by the results obtained in previous studies [15], where the study of hand contact pressure during 21 activities of daily living revealed high implication of specific palm spots. In fact, one of the main purposes of customizing the VMG30 glove was initially analyzing hand kinematics and pressure distribution in a combined way.…”

SoftSAR: The New Softer Side of Socially Assistive Robots—Soft Robotics with Social Human–Robot Interaction Skills

“…The expected force/pressure during pHRI with SARs can be a result of people touching, hugging, petting, and/or holding the robots or the robots actively initiating these behaviors. Tsetserukou et al [ 88 ] reported that human–human hugging can generate a pressure between 1.4 kPa and 5.9 kPa while Cepriá-Bernal et al [ 89 ] reported that human hand grasping can create pressure between 30 kPa and 270 kPa. As a result, soft pressure sensors would need to detect a minimum pressure range from 1.4 kPa to a maximum of 270 kPa.…”

Frustrated Total Internal Reflection Measurement System for Pilot Inceptor Grip Pressure

“…As such, it is understandable that considerable research effort has been put into measuring the exchanged actions between the hand and the manipulated object, with pressure being the most obvious target physical quantity. The most widespread sensing method is based on piezo-resistive pressure sensors [ 1 , 2 , 3 , 4 , 5 ], constituted by a matrix of sensing elements embedded in polymeric sheets. The method has proven its reliability and accuracy in countless applications and is the de facto industry standard.…”